Significant reduction in video bandwidth for storage and transmission purposes is desirable in various applications such as compact disc video and high-definition television. One type of video compression system which has received considerable attention lately is that proposed by the Moving Pictures Expert Group (MPEG), a committee within the International Standards Organization (ISO). The MPEG system is described in a paper entitled, "MPEG Video Simulation Model 3 (SM3)" by the Simulation Model Editorial Group, available from ISO as ISO-IEC/JTC1/SC2/WG11/N0010 MPEG 90/041, 1990 which is hereby incorporated by reference for its teachings on the MPEG video signal encoding method. This system is related to the conditional Motion Compensated Interpolation (CMCI) video encoding system described in U.S. Pat. No. 4,999,705 entitled THREE DIMENSIONAL MOTION COMPENSATED VIDEO CODING, which is hereby incorporated by reference for its teachings on video encoding techniques.
The MPEG system integrates a number of well-known data compression techniques into a single system. These include motion-compensated predictive coding, discrete cosine transformation (DCT), adaptive quantization and variable-length coding (VLC). In these systems, the adaptive quantization step is performed on the coefficient values produced by the discrete cosine transform operation for blocks of 64 pixels derived from the input image.
The DCT coefficients are quantized with varying resolution as a function of the amount of data generated by the encoding operation. If an individual image frame produces a relatively large amount of encoded data, the quantization step sizes applied to successive frames may need to be increased to reduce the amount of encoded data used to represent those frames, so that the average level of data produced over several frame intervals is able to be transmitted through a fixed-bandwidth channel.
If, when the quantizer is applying coarse quantization to the DCT coefficients, an image is encoded which includes an object having relatively few contours, the reproduced image of this object may have undesirable quantization distortion. This distortion would appear as an exaggeration of the contours in the object. In addition, if the object contains color areas which are saturated or close to being saturated, the quantization distortion in the reproduced image may cause undesirably large steps in saturation, causing the object to appear cartoon-like. This is especially true if these saturated or close-to-saturated colors are in the range of red to orange, since the human eye is more sensitive to detail in this color range than in other color ranges.
It is well known that the human eye is most sensitive to detail in color hues defined by the in-phase or I chrominance vector, as defined by the National Television Standards Committee (NTSC). In actual images, however, quantization distortion is more likely to be noticed in red objects than in objects having hues defined by the I chrominance vector, since in actual images, red objects will be more prevalent, have more highly saturated colors and have fewer contours than objects having reddish-orange hues defined by the I chrominance vector. Although I hues, such as flesh tones, are prevalent in many video images, they are generally present only at relatively low levels of saturation.